Daniel Kifer

Professor of Computer Science & Engineering

Daniel Kifer

Most Recent Publications

Answering Private Linear Queries Adaptively using the Common Mechanism

Yingtai Xaio, Guanhong Wang, D Zhang, Daniel Kifer, Proceedings of the VLDB

Backpropagation-Free Deep Learning with Recursive Local Representation Alignment

Alexander Ororbia, Ankur Mali, Daniel Kifer, C Giles, AAAI

A physics-informed clustering approach for ultrasonics-based nondestructive evaluation

Michail Skiadopoulos, Evan P. Bozek, Lalith Sai Srinivas Pillarisetti, Daniel Kifer, Parisa Shokouhi, 2025, Non-Destructive Testing

Pufferfish Privacy

Daniel Kifer, Ashwin Machanavajjhala, 2025, on p. 2020-2022

SENSITIVITY-CONSTRAINED FOURIER NEURAL OPERATORS FOR FORWARD AND INVERSE PROBLEMS IN PARAMETRIC DIFFERENTIAL EQUATIONS

Abdolmehdi Behroozi, Chaopeng Shen, Daniel Kifer, 2025, on p. 29663-29684

ℓ-Diversity

Johannes Gehrke, Daniel Kifer, Ashwin Machanavajjhala, 2025, on p. 1407-1410

Click Without Compromise: Online Advertising Measurement via Per User Differential Privacy

Yingtai Xiao, Jian Du, Shikun Zhang, Wanrong Zhang, Qian Yang, Danfeng Zhang, Daniel Kifer, 2025, on p. 2919-2937

RECONSTRUCTION ATTACKS ON AGGRESSIVE RELAXATIONS OF DIFFERENTIAL PRIVACY

Prottay Protivash, John Durrell, Daniel Kifer, Zeyu Ding, Danfeng Zhang, 2024, Journal of Privacy and Confidentiality on p. 1-33

GEOGRAPHIC SPINES IN THE 2020 CENSUS DISCLOSURE AVOIDANCE SYSTEM

Ryan Cumings-Menon, Robert Ashmead, Daniel Kifer, Philip Leclerc, Jeffrey Ocker, Michael Ratcliffe, Pavel Zhuravlev, John M. Abowd, 2024, Journal of Privacy and Confidentiality

Reply to Muralidhar et al., Kenny et al., and Hotz et al.: The benefits of engagement with external research teams

Ron S. Jarmin, John M. Abowd, Robert Ashmead, Ryan Cumings-Menon, Nathan Goldschlag, Michael Hawes, Sallie Ann Keller, Daniel Kifer, Philip Leclerc, Jerome P. Reiter, Rolando A. Rodríguez, Ian Schmutte, Victoria A. Velkoff, Pavel I. Zhuravlev, 2024, Proceedings of the National Academy of Sciences of the United States of America

Most-Cited Papers

Prolongation of SMAP to Spatiotemporally Seamless Coverage of Continental U.S. Using a Deep Learning Neural Network

Kuai Fang, Chaopeng Shen, Daniel Kifer, Xiao Yang, 2017, Geophysical Research Letters on p. 11,030-11,039

HESS Opinions: Incubating deep-learning-powered hydrologic science advances as a community

Chaopeng Shen, Eric Laloy, Amin Elshorbagy, Adrian Albert, Jerad Bales, Fi John Chang, Sangram Ganguly, Kuo Lin Hsu, Daniel Kifer, Zheng Fang, Kuai Fang, Dongfeng Li, Xiaodong Li, Wen Ping Tsai, 2018, Hydrology and Earth System Sciences on p. 5639-5656

Learning to extract semantic structure from documents using multimodal fully convolutional neural networks

Xiao Yang, Ersin Yumer, Paul Asente, Mike Kraley, Daniel Kifer, Clyde Giles, 2017, on p. 4342–4351

Differentiable modelling to unify machine learning and physical models for geosciences

Chaopeng Shen, Alison P. Appling, Pierre Gentine, Toshiyuki Bandai, Hoshin Gupta, Alexandre Tartakovsky, Marco Baity-Jesi, Fabrizio Fenicia, Daniel Kifer, Li Li, Xiaofeng Liu, Wei Ren, Yi Zheng, Ciaran J. Harman, Martyn Clark, Matthew Farthing, Dapeng Fang, Dapeng Feng, Praveen Kumar, Doaa Aboelyazeed, Farshid Rahmani, Yalan Song, Hylke E. Beck, Tadd Bindas, Dipankar Dwivedi, Kuai Fang, Marvin Höge, Chris Rackauckas, Binayak Mohanty, Tirthankar Roy, Chonggang Xu, Kathryn Lawson, 2023, Nature Reviews Earth and Environment on p. 552-567

Crime rate inference with big data

Hongjian Wang, Daniel Kifer, Corina Graif, Zhenhui Li, 2016, on p. 635-644

A Simple Baseline for Travel Time Estimation using Large-scale Trip Data

Hongjian Wang, Xianfeng Tang, Yu Hsuan Kuo, Daniel Kifer, Zhenhui Li, 2019, ACM Transactions on Intelligent Systems and Technology

A neural temporal model for human motion prediction

Anand Gopalakrishnan, Ankur Mali, Dan Kifer, Lee Giles, Alexander G. Ororbia, 2019, on p. 12108-12117

Learning to read irregular text with attention mechanisms

Xiao Yang, Dafang He, Zihan Zhou, Daniel Kifer, C. Lee Giles, 2017, on p. 3280-3286

Concentrated differentially private gradient descent with adaptive per-iteration privacy budget

Jaewoo Lee, Daniel Kifer, 2018, on p. 1656-1665

Detecting violations of differential privacy

Zeyu Ding, Yuxin Wang, Guanhong Wang, Danfeng Zhang, Daniel Kifer, 2018, on p. 475-489